23 citations · 101 across the 23 of their papers we have counts for
23 papers
STEP: State-Aware Task Estimation and Planning with Multi-Modal LLMs for Human-Robot Collaboration
Maitrey Gramopadhye, Prakash Baskaran, Xiao Liu +2
Effective human-robot collaboration in industrial settings requires robots to understand human intentions and assist with task planning, reducing workload. Recent works have explor…
PLUME: Probabilistic Latent Unified World Modeling and Parameter Estimation for Multi-Finger Manipulation
Abhinav Kumar, Soshi Iba, Rana Soltani Zarrin +1
Dexterous manipulation with multi-finger hands can be sensitive to physical parameters such as object shape, pose, and friction coefficients. While simulation enables large-scale d…
Geometrically Plausible Object Pose Refinement using Differentiable Simulation
Anil Zeybek, Rhys Newbury, Snehal Dikhale +3
State-of-the-art object pose estimation methods are prone to generating geometrically infeasible pose hypotheses. This problem is prevalent in dexterous manipulation, where estimat…
SUBTA: A Framework for Supported User-Guided Bimanual Teleoperation in Structured Assembly
Xiao Liu, Prakash Baskaran, Songpo Li +4
In human-robot collaboration, shared autonomy enhances human performance through precise, intuitive support. Effective robotic assistance requires accurately inferring human intent…
VisuoTactile 6D Pose Estimation of an In-Hand Object using Vision and Tactile Sensor Data
Snehal s. Dikhale, Karankumar Patel, Daksh Dhingra +4
Knowledge of the 6D pose of an object can benefit in-hand object manipulation. In-hand 6D object pose estimation is challenging because of heavy occlusion produced by the robot's g…
AVO: Amortized Value Optimization for Contact Mode Switching in Multi-Finger Manipulation
Adam Hung, Fan Yang, Abhinav Kumar +4
Dexterous manipulation tasks often require switching between different contact modes, such as rolling, sliding, sticking, or non-contact contact modes. When formulating dexterous m…
Diffusing Trajectory Optimization Problems for Recovery During Multi-Finger Manipulation
Abhinav Kumar, Fan Yang, Sergio Aguilera Marinovic +3
Multi-fingered hands are emerging as powerful platforms for performing fine manipulation tasks, including tool use. However, environmental perturbations or execution errors can imp…
CADRE: Dynamic Catching via Implicit Contact Descriptors and Task-Appropriate Recovery Affordances
Fan Yang, Zixuan Huang, Abhinav Kumar +4
Real-world dexterous manipulation often encounters unexpected errors and disturbances, which can lead to catastrophic failures, such as dropping the manipulated object. To address…
GeoDEx: A Unified Geometric Framework for Tactile Dexterous and Extrinsic Manipulation under Force Uncertainty
Sirui Chen, Sergio Aguilera Marinovic, Soshi Iba +1
Sense of touch that allows robots to detect contact and measure interaction forces enables them to perform challenging tasks such as grasping fragile objects or using tools. Tactil…
Diffusion-Informed Probabilistic Contact Search for Multi-Finger Manipulation
Abhinav Kumar, Thomas Power, Fan Yang +4
Planning contact-rich interactions for multi-finger manipulation is challenging due to the high-dimensionality and hybrid nature of dynamics. Recent advances in data-driven methods…
ResPilot: Teleoperated Finger Gaiting via Gaussian Process Residual Learning
Patrick Naughton, Jinda Cui, Karankumar Patel +1
Dexterous robot hand teleoperation allows for long-range transfer of human manipulation expertise, and could simultaneously provide a way for humans to teach these skills to robots…
HyperTaxel: Hyper-Resolution for Taxel-Based Tactile Signals Through Contrastive Learning
Hongyu Li, Snehal Dikhale, Jinda Cui +2
To achieve dexterity comparable to that of humans, robots must intelligently process tactile sensor data. Taxel-based tactile signals often have low spatial-resolution, with non-st…
Multi-finger Manipulation via Trajectory Optimization with Differentiable Rolling and Geometric Constraints
Fan Yang, Thomas Power, Sergio Aguilera Marinovic +3
Parameterizing finger rolling and finger-object contacts in a differentiable manner is important for formulating dexterous manipulation as a trajectory optimization problem. In con…
Hierarchical Deep Learning for Intention Estimation of Teleoperation Manipulation in Assembly Tasks
Mingyu Cai, Karankumar Patel, Soshi Iba +1
In human-robot collaboration, shared control presents an opportunity to teleoperate robotic manipulation to improve the efficiency of manufacturing and assembly processes. Robots a…
ViHOPE: Visuotactile In-Hand Object 6D Pose Estimation with Shape Completion
Hongyu Li, Snehal Dikhale, Soshi Iba +1
In this letter, we introduce ViHOPE, a novel framework for estimating the 6D pose of an in-hand object using visuotactile perception. Our key insight is that the accuracy of the 6D…
Hierarchical Graph Neural Networks for Proprioceptive 6D Pose Estimation of In-hand Objects
Alireza Rezazadeh, Snehal Dikhale, Soshi Iba +1
Robotic manipulation, in particular in-hand object manipulation, often requires an accurate estimate of the object's 6D pose. To improve the accuracy of the estimated pose, state-o…
Deep Tactile Experience: Estimating Tactile Sensor Output from Depth Sensor Data
Karankumar Patel, Soshi Iba, Nawid Jamali
Tactile sensing is inherently contact based. To use tactile data, robots need to make contact with the surface of an object. This is inefficient in applications where an agent need…
VisuoSpatial Foresight for Physical Sequential Fabric Manipulation
Ryan Hoque, Daniel Seita, Ashwin Balakrishna +6
Robotic fabric manipulation has applications in home robotics, textiles, senior care and surgery. Existing fabric manipulation techniques, however, are designed for specific tasks,…
Learning Dense Visual Correspondences in Simulation to Smooth and Fold Real Fabrics
Aditya Ganapathi, Priya Sundaresan, Brijen Thananjeyan +10
Robotic fabric manipulation is challenging due to the infinite dimensional configuration space, self-occlusion, and complex dynamics of fabrics. There has been significant prior wo…
VisuoSpatial Foresight for Multi-Step, Multi-Task Fabric Manipulation
Ryan Hoque, Daniel Seita, Ashwin Balakrishna +6
Robotic fabric manipulation has applications in home robotics, textiles, senior care and surgery. Existing fabric manipulation techniques, however, are designed for specific tasks,…
Deep Imitation Learning of Sequential Fabric Smoothing From an Algorithmic Supervisor
Daniel Seita, Aditya Ganapathi, Ryan Hoque +11
Sequential pulling policies to flatten and smooth fabrics have applications from surgery to manufacturing to home tasks such as bed making and folding clothes. Due to the complexit…
Dynamic Channel: A Planning Framework for Crowd Navigation
Chao Cao, Pete Trautman, Soshi Iba
Real-time navigation in dense human environments is a challenging problem in robotics. Most existing path planners fail to account for the dynamics of pedestrians because introduci…
Deep Transfer Learning of Pick Points on Fabric for Robot Bed-Making
Daniel Seita, Nawid Jamali, Michael Laskey +6
A fundamental challenge in manipulating fabric for clothes folding and textiles manufacturing is computing "pick points" to effectively modify the state of an uncertain manifold. W…